Data today is a valuable resource for companies, helping them stay competitive and innovate ahead to delight their customers.

However, while collecting enormous amounts of data across the different business units in a company is essential, it is but the first step towards actually making data-driven decisions.

Data might be the new oil, however, it is essentially a raw material that requires refinement by data analytics solution in order to be effectively utilized for decision-making.

In fact, big data use reached 53% in 2017, with telecom and financial services leading the way. In the long term, the global market for big data is poised to grow from US$70.5 billion in 2020 to over US$243 billion by 2027.

Making Sense of Data with Augmented Intelligence & Analytics

Traditionally, data analysis required companies to employ legions of highly-trained data analysts and scientists. This meant huge time and financial commitments to hire and train the IT teams to get up to speed.

Additionally, requests from data insights will have to go through a team of data analysts which will result in lag-times, likely resulting in lost opportunities due to outdated insights.

Thankfully, through the power of augmented analytics, organizations are able to get the insights they need – all without worrying about any data preparation, processing, and analyzing.

Augmented analytics goes beyond self-service business intelligence (BI) tools. Due to its machine learning capabilities coupled with natural language processing and automated insights, augmented intelligence allows data to be analyzed at scale to provide swift insights for timely decision-making.

Innovating Ahead in an Era of Disruption Requires Actionable Insights

Even before COVID-19 swept across the globe causing massive changes to the business landscape, innovators and disruptors across industries have long been actively utilizing data to get ahead of the curve.

And with augmented intelligence, raw data can be effectively ‘refined’ into actionable insights to fuel data-driven business decisions.

One example is Coca-Cola, which utilized AI-driven image recognition technology & augmented analytics to help analyze the data of how their products are mentioned and represented on social media.

Through the insights gleaned, Coca-Cola optimized the way they were serving social ads to its customer base, resulting in a clickthrough rate boost of 4x versus the other avenues of targeted advertising.

The COVID-19 pandemic has additionally wreaked havoc on the existing operations of companies that didn’t innovate, causing many traditional business models to fail.

Long-time industry giants such as Hertz had to file for bankruptcy in May 2020 as the coronavirus imposed lockdown restrictions, disrupting the traditional car rental business model – causing a majority of their existing revenue streams to dry up.

As businesses move towards an age where data is getting ubiquitous, swiftly utilizing it at scale could very well be the deciding factor between business can evolve and thrive in this new normal or face existential crises.

In the next section, we will be showcasing examples of how augmented intelligence can be utilized to solve pressing industry challenges and help businesses stay resilient in an environment of fierce competition and uncertainty.

7 Use Cases of How Augmented Intelligence & Analytics Can Help Drive Business Change

1. Retail: Capitalizing on Customers’ Shifting Needs

The retail industry today faces a mountain of challenges – from changing customer tastes to logistical and supply chain disruptions from the COVID-19 pandemic.

Through the power of augmented intelligence and analytics, retailers will be able to effectively harness their data to improve their operations from capitalizing on consumer trends to optimizing their inventory.

For example, if a retailer discovers their customers spending more for online pick-up orders like what Walmart and Target have experienced, they can analyze other key data across their organization to capitalize on this growing trend.

By analyzing their inventory movement and warehousing space data, retailers can capitalize on this trend by adding a pick-up option for other products on offer as well to capture more market share and sell more products without any supply delays or overstocking.

2. Financial Services: Helping to Acquire, Retain & Serve Customers Better

Financial institutions today are facing enormous pressure to innovate due to a combination of new fintech solutions, increased government regulations, and customers demanding better service and more personalized products.

Citigroup, for example, utilized augmented analytics to analyze their data to optimize their promotional spending campaigns. Allowing them to acquire new customers and better retain existing clients at a sustainable cost.

With augmented analytics, banks will be able to process and analyze key data such as their customer acquisition cost, customer lifetime value as well as the trends of products that are growing in popularity.

The insights gained will allow banks to correctly promote the right services to the right customer demographic utilizing an optimized budget to capture more market share.

In another case, a leading French bank, Crédit Mutuel, used augmented intelligence to help assist their advisors across 5,000 branches.

Through the power of augmented analytics, this augmented advisor analyzed 52,000 documents, allowing it to answer any client queries or relationship manager’s questions with accuracy in diverse scenarios from insurance to healthcare.

3. Airlines: Acting on Customer Preference & World Events

As one of the biggest affected industries from the COVID-19 fallout, airlines across the world are scrambling to stay afloat – and that means the need to manage costs while continuously delighting customers.

For example, Ryanair cleverly utilizes its customers’ personal preference data to offer targeted services and suggestions – such as offering a customer traveling with two children a family car for hire.

This helps to foster a greater sense of customer satisfaction while increasing opportunities to drive additional revenue through timely cross-sells.

Using augmented intelligence airlines will also be able to capitalize on customer travel plans, be it seasonal or because of a unique event.

For example, in 2017, many domestic travelers in America made hotel bookings to key states such as South Carolina and Wyoming in order to catch the solar eclipse on Monday 21st August.

Utilizing augmented intelligence, airlines would be able to swiftly analyze their operational data such as flight plans, aircraft availability, and hotel partnership rates in order to service the spike in travelers to these states and capture more revenue.

4. Hospitality: Driving Revenue Through Optimized Pricing

As we move into a post-COVID world, the hospitality industry, especially hoteliers, will be facing business challenges caused by a sustained decrease in air travel, increased health, and group size restrictions.

In fact, it is estimated that recovery to pre-COVID levels might only happen by 2023 for the hospitality industry. So how do hotels stay open and continue to keep business going?

Thankfully, hotels can effectively use augmented intelligence to analyze their booking data to drive more revenue in a time when it is most needed to stay afloat.

This can be done by analyzing their business-on-books (future bookings) and conducting a comparison versus their current inventory (number of rooms to sell) to adjust their pricing and bundling strategies based on spending patterns like the chart below.

This can also be further refined by analyzing more variables such as the company’s financials and revenue targets to ensure the sharpest pricing is offered to the customer while still remaining profitable.

This allows hotels to quickly pivot their offerings and pricings especially when customer demand plunges like during the end of 2020’s first quarter.

5. Telecommunications: Staying Competitive with an Evolving Customer Base

From providing internet services to phone networks, telecommunication companies are sitting on a treasure trove of big data from their customers’ usage to their business operations.

the generational shift of consumption habits is becoming more apparent – where younger users are increasingly spending more time online.

Additionally, apps such as Whatsapp are eating away at telcos’ traditional services such as voice and video calls. The pressure to innovate and evolve has never been more necessary.

With augmented intelligence, telcos can analyze their data to deliver insights into how to better bundle their services to meet the customers’ needs of today while retaining maximum profitability.

This means analyzing data around the cost of their services, from internet bandwidth to voice-call minutes, as well as customer usage trends of the same services, to develop different packages that are competitive and tailored towards each customer demographic.

6. Healthcare: Optimizing Operations for Better Patient Outcomes

As the cost of healthcare rises, patients are demanding newer payment models from their hospitals and there is a push towards a shared-savings approach that places greater emphasis on preventive care.

<Additionally, improving patient care outcomes is also mission-critical not just for the overall satisfaction of the patient but to drive more revenue for the hospital’s bottom line.

Thankfully with augmented analytics, hospitals will be able to optimize their operations by analyzing key metrics such as the length of stay and the bed occupancy rate.

The insights gathered will allow hospitals to better allocate hospital resources and optimize key ground operations such as the doctor & patient schedule timings.

7. Manufacturing: Pivoting Intelligently for Business Survival

The COVID-19 pandemic brought about big challenges that manufacturers are struggling to overcome.

From supply chain disruptions and a drop in worker supply to raw material shortages, manufacturers have to rely on the power of their data to stay competitive and innovate ahead.

One way manufacturers are surviving is by capitalizing on manufacturing trends and adapting their operations to meet the demands.

For example, while the coronavirus might have severely affected supply chains, the demand for face masks and shields has never been stronger.

Utilizing augmented analytics, manufacturers will be able to analyze key data such as the production capabilities of the production lines, the shipping timings, the schedules of their workforce, and their warehousing space availability.

The insights obtained will allow manufacturers to make a calculated pivot to start manufacturing products, such as face masks during the pandemic, that are in demand to bring in much-needed revenue to sustain the business.

augmented intelligence in manufacturing

Harness the Power of Augmented Intelligence & Analytics for Your Business

As we move into a world where data-driven decision-making is paramount to stay competitive, having a powerful data analytics solution is key to ensure success.

qbo, companies will be able to utilize the power of augmented analytics to gain actionable insights from their data.

Powered by conversational analytics, experience true data democratization with every user in your organization being able to tap onto the power of data by simply asking questions, like how you would in an everyday conversation.

Embark on a free 14-day trial today and unlock valuable insights for greater decision-making in your business.